Optimal siting of electric vehicle charging stations: A GIS-based fuzzy Multi-Criteria Decision Analysis

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dc.authoridERBAS, Mehmet/0000-0002-3002-6135
dc.authoridOzceylan, Eren/0000-0002-5213-6335
dc.authoridCetinkaya, Cihan/0000-0002-5899-8438
dc.contributor.authorErbas, Mehmet
dc.contributor.authorKabak, Mehmet
dc.contributor.authorOzceylan, Eren
dc.contributor.authorCetinkaya, Cihan
dc.date.accessioned2025-01-06T17:37:35Z
dc.date.available2025-01-06T17:37:35Z
dc.date.issued2018
dc.description.abstractElectric vehicles (EVs) are both economic and ecological vehicles which get their power from rechargeable batteries inside the car. Since they have a lot advantages as producing nearly no carbon emissions or pollution, being cost effective and less noisy; the main disadvantage of these vehicles are recharge related problems. One approach to deal with this problem is to construct electric vehicle charging stations (EVCS). A proper EVCS also should be located very carefully to maximize EV usage. Thus in this paper a geographic information system (GIS)-based MCDA approach is applied to address the EVCS site selection. Fuzzy analytical hierarchy process (AHP) and technique for order preference by similarity to ideal solution (TOPSIS) methods are applied to choose the optimal EVCS sites. A four-step solution approach is developed for the problem: (i) determination of 15 criteria from different perspectives, (ii) using GIS to assign EVCS site availability score, (iii) prioritizing the criteria using fuzzy AHP and finally (iv) ranking the potential sites by using TOPSIS. Proposed hybrid methodology is applied to Ankara (capital city of Turkey) as a case study. Results show that suggested alternative locations outperform the current locations of 12 EVCS in terms of considered criteria. (C) 2018 Elsevier Ltd. All rights reserved.
dc.description.sponsorshipRAGEP Award of the Science Academy in Turkey
dc.description.sponsorshipThe authors would like to thank intern engineers M. Erdogan Cevik, M. Ali Arslan, Izeddin Rezegmasri and Ilyass Ikouassen for their valuable contributions about criteria determination and evaluation. The authors also thank four anonymous reviewers and Subject Editor Dr. Xiliang Zhang whose comments have been helpful in improving an earlier version of the paper. Third author was supported by the RAGEP Award of the Science Academy in Turkey.
dc.identifier.doi10.1016/j.energy.2018.08.140
dc.identifier.endpage1031
dc.identifier.issn0360-5442
dc.identifier.issn1873-6785
dc.identifier.scopus2-s2.0-85053105698
dc.identifier.scopusqualityQ1
dc.identifier.startpage1017
dc.identifier.urihttps://doi.org/10.1016/j.energy.2018.08.140
dc.identifier.urihttps://hdl.handle.net/20.500.14669/2288
dc.identifier.volume163
dc.identifier.wosWOS:000448097800074
dc.identifier.wosqualityQ1
dc.indekslendigikaynakWeb of Science
dc.indekslendigikaynakScopus
dc.language.isoen
dc.publisherPergamon-Elsevier Science Ltd
dc.relation.ispartofEnergy
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanı
dc.rightsinfo:eu-repo/semantics/closedAccess
dc.snmzKA_20241211
dc.subjectElectric vehicle charging station
dc.subjectFuzzy AHP
dc.subjectTOPSIS
dc.subjectGIS
dc.subjectSite selection
dc.titleOptimal siting of electric vehicle charging stations: A GIS-based fuzzy Multi-Criteria Decision Analysis
dc.typeArticle

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